Concept
Compréhension du langage naturel
Cours associés (23)
CS-612: Topics in Natural Language Processing
This seminar course explores advanced topics in natural language processing through a mix of reading, reviewing, and writing academic papers.
ENV-420: Bio-engineering for rivers and natural systems
Démontrer les rôles et l'intérêt de la végétation riveraine des bords de milieux aquatiques. Notion de "génie biologique". Quand, pourquoi et comment utiliser les techniques de végétalisation? Demonst
EE-724: Human language technology: applications to information access
The Human Language Technology (HLT) course introduces methods and applications for language processing and generation, using statistical learning and neural networks.
CS-101: Advanced information, computation, communication I
Discrete mathematics is a discipline with applications to almost all areas of study. It provides a set of indispensable tools to computer science in particular. This course reviews (familiar) topics a
FIN-407: Machine learning in finance
This course aims to give an introduction to the application of machine learning to finance, focusing on the problems of portfolio optimization and hedging, as well as textual analysis. A particular fo
CS-552: Modern natural language processing
Natural language processing is ubiquitous in modern intelligent technologies, serving as a foundation for language translators, virtual assistants, search engines, and many more. In this course, stude
ENG-704: EECS Seminar: Advanced Topics in Machine Learning
Students learn about advanced topics in machine learning, artificial intelligence, optimization, and data science. Students also learn to interact with scientific work, analyze and understand strength
EE-608: Deep Learning For Natural Language Processing
The Deep Learning for NLP course provides an overview of neural network based methods applied to text. The focus is on models particularly suited to the properties of human language, such as categori
CS-431: Introduction to natural language processing
The objective of this course is to present the main models, formalisms and algorithms necessary for the development of applications in the field of natural language information processing. The concept
EE-559: Deep learning
This course explores how to design reliable discriminative and generative neural networks, the ethics of data acquisition and model deployment, as well as modern multi-modal models.